UK male life expectancy mapped, from Glasgow to Kensington

The data used in the Guardian article quoted from below, on how life expectancy varies across the country, deserved mapping. I’ve focused on UK male life expectancy, which according to the Office of National Statistics varies by 13.3 years between Glasgow (71.1 years) and Kensington and Chelsea (84.4 years).

Red pointers represent male life expectancy of less than 75; pink from 75 up to 77; yellow from 77 up to 79; green from 79 up to 81; and blue 81 and over.

If you click on a pointer, you can find out how much longer men in that area can expect to live than Glaswegians, and how much less than residents of Kensington and Chelsea (and tweet it if you wish). Female life expectancy is also included.

In Kensington and Chelsea, men can expect to live to 84.4 years and women to 89 – the highest figures for both London and the UK. The lowest age for men in the capital is found in Islington, who on average live nine years less, and for women it is Barking and Dagenham, with an eight year difference.

But the UK has much a much bigger gap, between the longest-living part of England’s largest city and Scotland’s. The ONS figures placed Glasgow city at the bottom of its lists for both men, who in the period 2007-09 recorded an average age of death of 71.1 years, and women, who lived on average to 77.5. That means lifespan differences between Kensington and Chelsea and Glasgow of 13.3 years for men and 11.5 for women.

It isn’t low spending: Scotland’s independently run NHS spends significantly more per person than England, although some of this is soaked up by the range of remote locations it has to serve. […] Some of Glasgow’s and Scotland’s low mortality ages seem to be down to specific health issues. A report published for the Scottish government in August found much higher levels of drinking (men drink 6.2 units a day north of the border, 4.3 in England), more smokers, fewer people eating the recommended five portions a day of fruit and vegetables and higher rates of obesity.